CXApp (NASDAQ:CXAI) released second-quarter financial results and hosted an earnings call on Thursday. Read the complete transcript below.
Benzinga APIs provide real-time access to earnings call transcripts and financial data. Visit https://www.benzinga.com/apis/ to learn more.
View the webcast at https://event.webcasts.com/starthere.jsp?ei=1772246&tp_key=a3b9300aa0
Summary
CXApp reported a transformative Q2 with a 79% revenue growth from $950,000 in Q1 to $1.7 million in Q2, driven by the Engine Room acquisition.
The company emphasized the strategic importance of CXApp 2.0, which focuses on enhancing enterprise AI applications from workplace context to personal and business growth intelligence.
CXApp 2.0 is now in deployment, and the company has secured significant multi-year contracts with Fortune 500 clients, illustrating strong enterprise retention and new customer wins.
The Engine Room acquisition added $8 million in revenue and $1.6 million of adjusted EBITDA, providing CXApp with mid-market distribution channels and cross-selling opportunities.
Management is focused on scaling recurring revenue, leveraging synergies from the Engine Room acquisition, and targeting break-even by the second half of 2027.
CXApp’s AI-powered platform aims to reduce operational friction in enterprise environments, focusing on user experience and seamless integration of workplace solutions.
The company plans to expand its market presence through strategic partnerships, including a significant role for Google Cloud in supporting its infrastructure and marketplace distribution.
Full Transcript
Karim, CEO
With Zoe, which I’m hopefully you’re going to enjoy her perspective and we’re close, so it’s going to be a packed agenda. I know a lot of you have been sending some questions. We’ll take some questions in the Q&A section as well, so I appreciate that. So with that, let’s get going with the business. So let’s talk about our Q2 earnings and as I said earlier, the three themes. Number one, Engine Room is transformative. Number two, CXApp 2.0 is real, is available.
And third, we’re now seeing a clear operating model for translating growth into operating leverage and ultimately profitable growth. And we at CXApp are building the agentic AI operating layer. So before we go into the business numbers, let me talk to you guys about the—just make sure you have the disclaimer slide on what are the forward-looking statements. Make sure you read the safe harbor. Please review the safe harbor non-GAAP disclosures in today’s presentation and our SEC filings for the applicable risk assumptions and reconciliations.
We will be filing the 10-Q tomorrow and so you can read that when you get that. So let me talk about, you know, the company we have today, right? And the company we have today is pretty amazing. We are deployed globally around 200 plus cities with more than 60 plus customers now supporting a large installed base of users. We operate inside demanding enterprise environments where security, privacy, reliability, integration are not optional, they’re necessary.
This matters because our AI strategy starts from something valuable: enterprise trust and real operating context. Context is very important. We aren’t beginning by building an AI application and trying to figure out where it fits. We already operate inside the enterprise. We understand people, places, workflows and enterprise systems. And CXApp 2.0 is about making that context increasingly intelligent and actionable. So we’re headquartered in the San Francisco Bay Area.
As you know, we have teams in Toronto and Manila. And now we’re excited to welcome the Australian team which is headquartered out of Melbourne, but they’re all across Australia as well in New Zealand. We’re excited to have them on board, and this gives us the global coverage. We have around 70 team members now globally and they’re all working hard in making AI successful in the enterprise market that we’re in. Before we get to the numbers, let me just give you context of where we’ve been and where we’re going.
So CXApp 1.0 established the enterprise foundation. It showed us that we have great software, workplace software that has people and place intelligence. We have Fortune 500 customers. They have high-trust, high-complexity deployments. This remains an important part of business. We made some significant strides in the last two quarters. Chris is going to talk about those customer case studies and stuff, but it’s been amazing there. But CXApp 2.0 really expands that opportunity.
We’re moving primarily from understanding places, which is really the Flow product, which is where and how people work, to person, which is what we’re calling Beat—what an individual and team need to accomplish and what should happen next in your life as a worker. Now we’re moving with Engine Room into business: how companies acquire customers, convert demand and grow. That business context is significantly strengthened by Engine Room. As you know, underneath those experiences is the same CXApp agentic platform.
The strategy for me here is very straightforward: proven enterprise technology, mid-market distribution, prioritize AI and scale recurring revenue. We’re going to run that flywheel cycle because we’ve got now an agentic platform that we can leverage across multiple verticals. And more importantly, we now have a new distribution mechanism through Engine Room. So this is the transformation I’m talking about. This is what we’re executing on and we’re super excited about this opportunity.
So let me go into the business for this quarter and what happened this quarter. So this is a pretty exciting time for CXApp. As you can see in our highlights for the quarter, there are six main highlights, but the biggest one is the Engine Room transaction. It is transformative. I’m going to talk more about it in detail, but it really did change the revenue trajectory for the company, and more importantly, quarter-over-quarter increase of probably 79% revenue growth from $950,000 in Q1 to approximately $1.7 million in Q2.
The more important thing is what sits underneath that growth. Enterprise retention remains strong. Two major Fortune 500 customers renewed their relationship with CXApp. In enterprise software, renewals matter enormously because they value the product. After the initial sale, customers that continue to choose CXApp. We also added a significant new win in the financial services sector. This is a three-year multimillion-dollar recurring revenue deal.
It went through a very competitive RFP. We’re super excited to have that customer on board and they’re scaling with us beginning this quarter, and it’s a really, really important win for the team. And it’s one for two reasons. First, it demonstrates continued demand from highly sophisticated, regulated customers. Secondly, these are the types of customers where CXApp 2.0 can expand over time across additional modules, users and AI capabilities. The other big achievement for this quarter is we moved CXApp 2.0 into deployment.
That’s a big win for us. The progression is win, deploy, adopt, expand—exactly what we want to replicate with 2.0. Really what we get is an agentic AI platform that allows a user to navigate their workplace, navigate their work and navigate their experiences across the whole enterprise. That’s very exciting. Our customers, the reason why they’re selecting us is because we have CXApp 2.0. The wins we got, the renewals we got are all because of CXApp 2.0.
And as you know, during the quarter we completed the Engine Room transaction. So for Q2 we only have one month because it was the month of June that Engine Room is part of the revenue. And it’s been an amazing one month because they’ve continued to get new clients, they’ve got double-digit growth, they’re going through this annual process where they’ve got commitments from existing clients. So it’s been really good. And so all of these six factors combined really have been super successful for the company.
I want to congratulate the team on the job well done, and it builds the momentum, it strengthens the foundation for CXApp 2.0 and our scale growth moving forward. So let me tell you a little bit about Engine Room and what better than just to roll a video? So, operator, if you can roll the— All right, cool. That’s pretty exciting. So when I talk about Engine Room, I talk about it as being transformative, and as you can see from the video, it’s pretty exciting stuff they do and they’ve been at it for 13 years and they’ve made amazing progress in getting clients and making sure that they have really solid footing. So let me tell you why this is transformative. Engine Room does not simply add revenue; it changes the starting point for CXApp.
Engine Room brings more than $8 million of revenue, approximately $1.6 million of adjusted EBITDA, a highly recurring revenue profile and more than 50 mid-market customer relationships. But strategically, three things matter even more for me. Number one, distribution. CXApp historically sold into large enterprises through an enterprise sales process. Engine Room gives us trusted relationships with dozens of mid-market businesses. That gives us a much faster proving ground and future distribution channel for CXApp AI products.
Number two, business context. As I said earlier, CXApp already understands workplace and employee context and that’s one of our moats and differentiation. Engine Room brings customer acquisition, performance marketing and growth data that allows CXApp 2.0 to expand from understanding how people work to understanding how businesses grow. Number three, cross-sell. We can introduce CXApp capabilities into Engine Room’s customer base and we can introduce Engine Room’s growth capability into CXApp’s enterprise products.
The combined company has an enterprise anchor, a mid-market growth engine and a shared agentic AI platform. And the combination moves CXApp to more than $12 million of annualized revenue scale. This acquisition created scale. Our job now is to turn that scale into operating leverage. So I’m super excited about this. I think this is the right move for the company. It positions us ready for the growth engine that we’ve been talking about, the double-digit growth.
It gives us that flexibility in terms of having, you know, the ability to innovate in a very interesting market—Australia. I’ll talk more about that in the investor forum we will have. We’ll go more deeper into it. But I just want to share this story with you and share with you that this has been an amazing, amazing transaction for us. So with that I want to move on to the financials for Q2. You know, I’m going to turn it over to Melissa to walk through the quarter in more detail.
As you listen to the financial results, I would focus on one important relationship: how rapidly the revenue base is changing relative to the cost structure. Melissa, all yours.
Melissa, CFO
Thanks, Karim. So the quarter-over-quarter comparisons demonstrate that step change is taking place in the business between Q1 and Q2. Revenue has increased approximately $950,000 in Q1 to $1.7 million in Q2, representing, as Karim previously mentioned, a 79% sequential growth. Our annual recurring revenue has increased from $3.6 million to $11.5 million.
Oh, one second. We’ve jumped. Let me just find that slide again. Sorry about that. Net revenue retention has increased from approximately 98% to 99.3%, continuing to demonstrate our strong retention across installed bases. Total assets increased from approximately $33 million to $36 million and our cash EBITDA improved from approximately negative $3 million in quarter one to negative $2.68 million in quarter two. EPS was approximately negative $0.50 compared with negative $0.09 in Q1.
So the key takeaway quarter over quarter is that the revenue base increased substantially while cash EBITDA improved modestly. We’re still investing in integration and development of the combined businesses, but the operating model is beginning to show greater scale. The year-over-year comparison also shows meaningful progress. Revenue increased approximately 42% from $1.2 million in Q2 of 2025 to $1.7 million this quarter. ARR increases from $4.5 million to, again, the $11.5 million, an increase of approximately 156%.
Net revenue retention increased by more than 5 percentage points to approximately 99.3%. Assets also increased 22% from $29.6 million to approximately $36 million. Cash EBITDA was approximately negative $2.7 million, which is a neutral position compared to a year ago. And EPS has improved from approximately negative $0.16 to negative $0.10 between the two years. The most significant change in the financial profile is therefore the scale of the recurring revenue base while we continue to manage investments required to support integration and future growth.
And now let me put this cost structure into perspective. Total operating expenses increased approximately $275,000 quarter over quarter, or 5.6%. However, we do need to compare that with the approximately 79% sequential revenue growth. The increase in operating costs was driven primarily by the Engine Room acquisition and associated operating activity. Importantly, these Q2 numbers do not yet reflect the benefit of the operating synergies we are implementing as we integrate the businesses.
Our focus moving forward is straightforward: grow revenue faster than expenses. We expect to accomplish that through shared functions, tighter operating discipline, productized implementation, increasing automation, and a higher recurring software contribution. That operating leverage is central to the financial strategy for the combined company. And I’ll turn it back to Karim now.
Karim, CEO
Thank you, Melissa. I apologize, I was on mute. This was a really great quarter. As you can see, we are finally showing the value of our technology platform, but also the Engine Room acquisition position. But I want to put in perspective on what I see the value of this company as we move forward. And this valuation is based on numbers that we get from KeyBank, which does a monthly survey on software benchmarks and looks at all the recurring revenue-based businesses and software businesses.
So as I think of our business now, it is an AI-powered software business that is at much larger scale. And the scale, as you know, last quarter we were at a million a quarter. This quarter we are now $1.7 million a quarter. And with the full Engine Room integration we will be hitting $3 million a quarter, or $12 million annualized, by next quarter. And that shows real growth as well as shows real momentum and scale. And based on that, when you think about that business and you think about that software business with the metrics we have, you know, just on a conservative basis, it’s a 9.7x multiple, right?
That’s more on next 12 months revenue. I’m just saying that revenue we have now, we will have now by Q3. So to me, we’re at a very attractive stock price right now given where we’re at in terms of the valuation that we should command. I do believe that we will continue to perform and, given our double-digit growth strategy, we believe by second half of 2027 we will be growing and getting to the breakeven point. And that’s where our focus is. Our focus is really to get to that level and you can see the metrics based on that.
This is all illustrative, by the way. This is not a valuation guidance. I’m just taking industry benchmarks and showing you what the value of this company is. And the fact that we’ve now built that agentic platform, that R&D expense has been done and now it’s about growth and distribution. And this is where we did the Engine Room transaction and this is where we feel very strongly about the growth and scale of the business. You know, can we sustain this growth?
Can we increase software mix? Can we translate into greater revenue scale? Absolutely. And that’s where, you know, the two businesses have been complementary. But we’re going to help each other scale up faster. Now let me talk about, you know, probably one of the most important charts in the slide deck here: it’s about the path to break even, right? And again, this is a directional operating framework, not specific financial guidance. The Engine Room acquisition gives us a combined revenue of more than $12 million.
From here there are several identifiable levers. First, organic growth: continue expanding the CXApp enterprise business and Engine Room’s customer base. That’s obvious. Second is cross-sell: introduce additional CXApp modules into existing enterprise customers. Chris is going to talk a lot about that today. Number two is introduce CXApp generative AI products into the Engine Room’s mid-market customer relationship, though that’s the second cross-sell that we think is very important.
Thirdly, increase software monetization. We’ll talk about Flow, we’ll talk about Analytics Events, and our emerging personal execution capabilities called Beat. Increase our opportunity to generate recurring software revenue from the same platform. And fourth, prioritize that mid-market motion for mid-market customers. We don’t want to recreate a long enterprise implementation. Our objective is to standardize the products, standardize the connectors, faster provisioning, and lower cost to serve.
Fifth, operating leverage. We now have opportunities to share infrastructure, technology, corporate functions, and delivery capabilities across a much larger revenue base. That’s the synergy that Melissa talked about. The operating model we are working towards is characterized by, number one, double-digit revenue growth, which is part of our strategy as well as what Engine Room is already on; number two, recurring revenue more than 95%; gross margin above 70%; software mix above 95%; increasing revenue per customer. We’re already at $150,000 to $200,000 per client per year, which is really great. And a disciplined expense growth, which now we can do with the larger scale. If we execute against those levers, we believe there’s a credible path towards break even in the second half of 2027, followed by profitable growth. So I want to now close with why CXApp? Why do you want to continue to invest and be part of this journey?
Why is this moment different for CXApp? Reason number one, Engine Room is transformative. It immediately increases our revenue scale. It gives us profitable operating capability and, perhaps more importantly, it gives CXApp a mid-market distribution engine that we did not previously have. Reason number two, CXApp 2.0 is now in production. This is no longer simply a roadmap or an AI narrative. We are ready now to deploy this across our clients. We’ve been successful in the demonstrations and prototypes and getting it through our clients.
They’re going through a lot of validation. But now it is launching, it is launching live with a new client. It’s also launching live with existing clients. And now we have these new enterprise logos signing multi-year agreements. They would not be signing multi-year agreements with us unless they knew that the roadmap and the product we have is going to be long-lasting and for the future. And we are expanding the platform from workplace intelligence to personal execution, which is Beat, as well as the growth intelligence, which is Engine Room.
And reason number three, the financial model is becoming more scalable. Q2 revenue increased approximately 79% sequentially while operating expense increased approximately 5.6%. That does not mean the work is finished—far from it. But it demonstrates the opportunity for operating leverage as we integrate the businesses, grow recurring revenue, and prioritize more of what we offer. So with that I’m going to look into some questions that have come in.
Let me see. Okay, question number one. Good question. How much cash do you have? What are your liabilities after the purchase of Engine Room? I’m going to have Melissa take that.
Melissa, CFO
Thanks, Karim. So our cash as of 30 June 2026 is $11.7 million. Most importantly, the acquisition costs have been—acquisition costs related to Engine Room have been largely paid and any subsequent funds owing on the acquisition of Engine Room are tied to an earn-out model.
Karim, CEO
I don’t know. That’s good. So I think just to be clear, you know, the Engine Room acquisition was 65% cash and the rest was in earn-out. So the team is focused on—it’s a two-year earn-out with growth factors in revenue specifically. So that’s going to earn out itself. So we have no other liabilities on Engine Room except the earn-out. And overall, as you can see, the asset base has increased and it has been a very successful integration up to now.
So Okay, next question I see is, how quickly should shareholders expect the Engine Room acquisition to be reflected in CXApp’s reported revenue? Mel, you want to take that?
Melissa, CFO
Yeah. So we’ve actually already captured one month of combined revenues, that being the month of June. We will be able to demonstrate next quarter, so Q3, the full combined impact over the three months of that acquisition and the combined revenue.
Karim, CEO
Okay, I think the next question was one more question. What do you think of the revenue growth over the next 12 months? So look, I gave you some illustrative graph on our potential. As you know, we are focused on double-digit growth. We really believe that the scale we’re getting with Engine Room, the wins we have with our existing enterprise business and new logos coming in that are multi-year, multi-million-dollar contracts, we’re pretty, pretty positive on that.
And we’re also positive on Engine Room because they’ve also increased their—they’ve increased their revenue profile, the number of clients, and their annuals process has been super successful. So anyway, we are pretty positive on that. I think our goal is, like I said, is to have break even by second half of 2027 if we execute our plans that we have and the growth vectors that we’re working on. I’m pretty confident in that. And we’re also focused on expense management and, you know, with agentic AI, we’re leveraging AI across our enterprise.
All our functions are using AI so we’re seeing a lot of efficiency there. As you can see in terms of our team members, we’re very cost efficient. And so I’m pretty positive that in the next 12 months we will achieve much higher growth and we will get to the breakeven target that we have. So. Okay, we’re running to the end of the call here, so thank you everybody, I appreciate it. We’re going to take a brief pause and we’ll join you back in 60 seconds or so for the investor forum.
Thank you. All right, it’s 2:30pm Pacific, 5:30pm Eastern. Welcome to the investor forum. Thank you. For people who joined the earnings call a few minutes ago, we’re going to be more strategic here, more product focused, really talk to you about the products, the business, the customers, the things underneath the hood that we’re working on, and show you the path that we believe is going to be super successful for CXApp. I think we shared the agenda before. I’m going to start off with the strategic view of the business and more strategically thinking about where we’re at, where we’re going.
And then the team is going to tell you how we’re doing, what we’re doing, what we plan to do next, and then we’ll end up with a very interesting fireside chat. Thank you for being here. And we wish to do this next time live in person, but we’re going to do the best to do these demonstrations and these discussions on the webcast. Number one, I want to start with something I believe very strongly. I’ve been involved in lots of technology transitions.
I was involved in the first mobile phone, I was involved in the first 4G network, was involved in the first Wi‑Fi systems, and then I was involved in 5G and cloud, and all these interesting technology developments that have happened. And I believe we are at the beginning of another major technology transition in enterprise software. What I mean by that is CXApp started by solving a very real problem, how people interact with the workplace. That happened after the pandemic.
As you know, COVID created this hybrid environment. What we have built underneath that experience is becoming much bigger than a workplace application. We have enterprise integrations, we have proprietary context, we have AI orchestration, we have data, and we have security and trust. Now we’re bringing all these assets together into CXApp 2.0, an agentic AI operating layer. Our strategy has three priorities. Number one, reposition CXApp around this agentic operating layer, which I talked about, is the context layer.
Second, use Engine Room to give us immediate scale, mid‑market distribution, and a much larger customer base. And thirdly, prioritize what we learn into repeatable vertical AI solutions. This is not simply an evolution of our product. I believe it can be an evolution of the company. We’re going to talk about that. We’re going to go through some real strategic focus on why we’re doing this. Let me explain why the timing is important in the industry right now.
Enterprise software is evolving as we speak. The first generation of enterprise software created systems of record. Then SaaS and analytics gave us applications, dashboards, and visibility. But visibility is no longer enough. The next generation of enterprise software is about action, about getting stuff done. Basically, AI agents will increasingly understand context, make recommendations, coordinate workflows, and actually complete outcomes. That is the layer I want CXApp to own.
Not another chatbot, not another dashboard, not another AI feature added onto an application. The operating layer between the enterprise systems, its data, its people, and the actions that need to happen next. Employees want fewer applications, executives want decisions rather than more dashboards, and mid‑market businesses want practical AI that produces value today without having to assemble teams of AI engineers to build it themselves. This is the opportunity that we are designing CXApp around.
We’re building the agentic AI layer for enterprises to work and grow. And that is our focus. Let me put it into a little bit more detail and show you what I mean by that. This slide shows me where we came from and where we’re going. We started with Place. Flow understands where and how people work — workplaces, spaces, resources, presence and experiences, and maps and locations. Now we are moving into Person with Beat. Beat is about personal and team execution.
What do I need to accomplish? What has changed? What matters most right now? What should happen next? How am I going to become more productive? Eventually, what can the platform safely do for me? Right. In an enterprise you want to be in a secure environment. You want to be able to get your stuff done. Now we’re adding Business through Engine Room. How does the company find customers? How does it convert demand? Where is the marketing working? Where is it not working?
What is the revenue being lost? All those questions need to get answered, and what action should happen next to grow the business? So think about what we’re assembling. Place gives us workplace context. Beat gives us personal and team context. Engine Room gives us customer and growth context. Underneath all these three is one shared CXApp platform. It senses, it prioritizes, it acts, it verifies, and critically it learns, and also it gets it done.
We’re about the outcome business. We’re about context — not just another insight. Context should lead to an outcome. And this is what we’re focused on in really creating those amazing outcomes for our clients. So next I’m going to talk about the market, right? So, you know, this is studies taken from one of the vendors, Grand View Research. And, you know, you look at the market surrounding this strategy. Amazing. We’re participating in three large categories that are all growing: digital workplace platforms, enterprise agentic AI, and now marketing automation and growth intelligence.
The individual market growth shown here are significant, but the bigger number is the compounding effect — it’s a 75x compounding effect of growth over the next couple of years into 2030. It is not claimed that our addressable market sometimes becomes 75%, but the opportunity for us is 75x. So we’re not exposed to only one category; now we’re exposed to three categories. We sit in the intersection of workplace intelligence, agentic AI, and business growth intelligence.
My conviction is that the intersection matters because enterprises don’t ultimately buy AI because AI is interesting. They buy it to make employees more productive, make better decisions, reduce costs, and grow revenue. These are precisely the outcomes that these three businesses allow us to attack together. So let me talk about what are we building, and we spend a lot of energy and time with our Silicon Valley team, and as we integrate our folks in Australia, they’ve also been thinking about it.
And the reality is all great minds think together, and we’ve had a great interaction with our teams. This gets to the heart of what we’re building. Across the top, you see the context domains — the work intelligence, the place and person, the growth intelligence, the business, and the future verticals that we can add over time. But I want you to focus on what’s underneath. This is the CXApp agentic platform. The philosophy is simple: understand the context, recommend the action, get the right approval, complete the outcome.
As I mentioned in previous events, Bond is our agentic engine. Bond is a multimodal, multi‑agent orchestration system that provides the agentic execution capability. Cortex provides intelligence — context, knowledge graphs, personalization, analytics — and we surround that with the requirements enterprises actually care about. They care about identity, they care about auditability, they care about human control, they care about connectors, they care about governance, they care about all the things that are important to make an enterprise successful.
That’s why we have designed this for the enterprise. We’ve designed it with all those controls, and we also integrate with all our partners, all our cloud partners. As you know, we have a strong relation with Google Cloud, also partnering with AWS, and we have also one of our clients using Azure. So we are multi‑cloud. We have access to all their models, all their information, and we’re using the best‑in‑class technology to deliver this agentic operating layer.
And the most important part of that discussion is we’re not betting CXApp on one foundational AI model. Models will change, models will get cheaper, models will become more powerful. Our value is the enterprise context, orchestration, permissions, actions, and outcomes layer from these models. That’s why I call it the operating layer. The model can provide intelligence. CXApp makes that intelligence useful inside the enterprise. We are the outcomes, we are the actions, and that’s what we’re focused on.
Another key part of this, as we looked at Engine Room and other opportunities to partner with folks, is that this architecture that we built gives us tremendous leverage. We don’t have to build a completely different technology stack every time we enter a new use case. The same orchestration layer can support workplace agents, can support growth agents, analytics agents, automation agents, and eventually industry‑specific agents. A meeting agent and an attribution agent may solve very different customer problems, but underneath they need many of the same capabilities.
They need the data, they need the context, they need the permissions, they need the workflow orchestration. They need auditability and the ability to complete work in the system where that work belongs. That is where I believe the leverage comes from. One platform, many specialized agents, real business outcomes. The more repeatable those agents become, the more efficiently we can take them to the mid‑market. So that’s where we’re really focused on — we built a really strong technology architecture, and now we’re looking for, with that amazing product, we’re looking for the distribution model.
And this is where our new friends at Engine Room come in. As I think about Engine Room, I think I mentioned it in the earnings call, but I want to reiterate it is strategically super important for us. It is simply not an acquisition that added revenue. Engine Room changes how we can take CXApp to market. CXApp gives us the enterprise anchor technology proven in complex environments. Engine Room gives us a mid‑market customer base, recurring revenue, commercial data, and people who understand how to drive measurable business outcomes.
Australia gives us an excellent launch pad. We can launch, learn, and scale. We can work directly with businesses in trades and field services, construction, automotive, healthcare, professional services, and manufacturing. These are incredibly important parts of the real economy. A plumber doesn’t need another chatbot. A construction company doesn’t need another AI demonstration. A healthcare operator doesn’t need another dashboard. They’re very practical folks.
They need more customers, they need faster response, they need better scheduling, they need lower acquisition cost, they need higher employee productivity, they need better visibility into what is driving revenue. This is where practical vertical AI becomes incredibly powerful. Engine Room gives us more than 50 customer relationships and a recurring revenue foundation. Our objective is to identify the workflows and repeatedly create value, prioritize them on the CXApp platform, and distribute them more broadly.
Services help us discover the problem. Software gives us the scale. So this is why I’m super excited about Engine Room. It’s getting us a head start into the mid‑market strategy that we’ve had. We’re working closely with them this quarter to start identifying customers. There’s already been a lot of great interest, and as we get Flow and Beat and Events and other products that Chris is going to go through, there’s a huge opportunity to leverage that channel.
All right, so next let me talk about a little bit more detail about the combined platform, right. You know, all of these strategies and these product visions ultimately have to translate into economics. And I’m going to go a little bit more deeper — I know I went a little bit on the earnings call — but the acquisition gave us the scale. It gave us that $12 million in revenue. Now CXApp 2.0 has to give us operating leverage. Today we have that combined revenue north of $12 million.
We have enterprise customers on the CXApp side. We’re growing those customers. We have those 50 mid‑market relationships through Engine Room. We have recurring revenue, we have data, we have distribution. The next phase is about pulling four levers. Number one lever is grow and expand existing businesses. And both businesses are really working really well. The enterprise business is expanding, and Engine Room customer growth is happening. Secondly, cross‑sell and distribute across the combined customers.
That’s job one, and we’re doing that right now as we speak. Third is the exciting part of prioritizing the AI and new modules — increasing the software component of our revenue, which is already 95%, but now growing it in the new AI economy. And fourth, training the operating leverage as the company scales. And we talked about it’s already starting to show the signs in Q2 here. This means that ultimately revenue should grow faster than the infrastructure required to support it.
Our ambition is very clear: higher recurring revenue, higher software mix, higher gross margins, more revenue per customer, and a path towards break‑even and then profitable growth. So the acquisition created the scale, the platform has to create the leverage, and that’s what we’re focused on executing. And I’m pretty excited that this is a path that we’re on. As I said on the earnings call, we have all those metrics. We’re diligently working on them.
As part of the integration, I’m showing some directional synergy targets that the team has. We’re already realizing some of those synergy targets in the second half this year. Next year we believe there will be more, not only on cost synergy, but also revenue synergy. And then finally the flywheel effect with the CXApp 2.0 product will really implement much higher growth factors here. All of this is great plans, but none of it really happens unless I have a great team to execute.
I’m super excited to introduce some of the team members here. We’re working on a very lean operating model. Chris is running enterprise business in North America for us. Adam is taking on Australasia as well as the Engine Room business. And then Melissa has stepped up as being our interim CFO. We’re also proud to have a global CTO team that brings together technical leadership across Silicon Valley, Canada, Australia, and Southeast Asia. And that is important.
AI innovation is global. Our customers are global. Our engineering capability should be global as well. This structure is designed around speed, accountability, and execution. We don’t want any unnecessary organizational layers. We want talented people close to the customers globally, close to technology, and close to the results. That’s where we believe we have a huge opportunity. And so, anyway, I’m super excited to introduce the team. So I’m going to transition now to Chris, who’s going to talk about the North American enterprise business.
Chris, go ahead.
Chris Wiegand, General Manager, North America
Well, thank you, Karim, and welcome all. Chris Wiegand, and I’m General Manager in North America. I’ll let you know, I am an entrepreneur at heart and I couldn’t tell you how excited I am about this whole AI transformation. It’s truly changing things, as I’m sure you have in your personal life, but especially in the workplaces. And what’s also exciting, just on the tail of that, we’ve had the best year we’ve ever had. We’ve signed the largest deals.
I’m going to take you through. We’ve got our 2.0 product deployed and working. We’ve got a new module I want to tell you about in our events. And then Karim also told you a little bit about the new product Beat. So Karim’s been telling you all about strategy and what our vision is. What I want to do for the next 20 minutes, I’m going to tell you through what’s happening on the ground, how are we doing our business, what are the customers all about?
And most importantly, we’ve got some live videos that we’ve recorded to show you the product itself. And then we’re going to go through and talk about, you know, what’s the rest of the year look like and how are we going to do it? Okay, so what I really want to emphasize here is, you know, there’s not names on the page, but these are the largest and biggest companies in the world. Some of them, they’re leaders in their space. And I’ll tell you this, they have gone through super diligent, super diligence, we’ll call it.
These are some of the toughest RFPs and diligence processes you can go through. And that’s how it should be. Right? We’re working with very secure, complex environments. And so by these customers doing this, they’ve really gone out to market. They have the resources, they can choose whoever they want to. And by sandbox trials, by many, many questions and answers and meetings, we’ve come out on top. So that’s the pattern I really want you to know is that we keep winning in the regulated environments, the enterprise environments.
And these are again some of the toughest places to get your products deployed. I’ll take you through from left to right here. One of our biggest wins this year is a top financial institution. They are actually global. They’ve got dozens of sites around the world, thousands of users that are going to be coming online. This is actually more than a 12-month pursuit. And again they went out to market and CXApp came out on top. Next we have a global asset manager.
So we’re closing this right now. They’re starting at the end of this year so there’s going to be a quick turn on their implementation. Again, five-figure number of users, very similar use cases in terms of what they’re doing. And again they’re starting with an entire population that we’re going to go live with. Next is a leading US insurer. I’m going to spend a little bit more time on this because it’s going to tell you about how we deploy. This is an interesting customer for many reasons.
One, it’s really our bridge to the mid market. It’s a few thousand users. We’re still in an enterprise environment but this is how we really took our product and decided and learned how are we going to productize this? So we’re configuring, not making custom code. I’m going to talk more about that. And they’re going to go live in September. They’ve got a brand new headquarters and we’re in deployment testing for that right now. And then let’s not forget our amazing install base.
We’ve got enterprise customers today that are choosing to stay with us. Same rigorous environments. We had one of our largest financial services customers renew. We had our largest media and entertainment company. They renewed and expanded. And so where is this all going? This is all leading to more revenue. That’s the goal. And so not giving you guidance, but directionally the new customers are coming online. The things that we’re not even seeing yet in terms of revenue, it’s about a third uplift.
So that’s pretty significant when you think about it. And in addition to the other things I’m going to talk you through here. All right, so validation is really the key here, you can go win these deals, but you have to deliver them. And that’s really what our customers are expecting is exactly what we’re doing. So this is the company I’m going to take you through sort of a quick timeline of how we’re delivering for this leading US insurer. And again, it’s a brand new headquarters for them.
So it starts out we have an enterprise agreement and this is very detailed scope of work. We understand exactly what we’re delivering, how we’re going to do it, and then we go and build it. So with that we have integrations into their core systems. Remember, the core value of what we do here in CXApp is we’re taking disparate systems and we’re putting it all into one cohesive system that an employee can just get what they need quickly and easily.
You’re going to see that in the demo. Now we’re in testing so we deployed 2.0 to them. We’ve got most of the integrations done with a brand new headquarters. As you can imagine, there’s things that are staged. So right in the next 30 days we’ve got really important next steps in terms of finalizing testing. But I can tell you the client is extremely happy. We’re right on schedule and then we’re going to scale that goes live to the population. There’s a few really important points I want you to remember here.
This is our point that we’ve really transitioned from custom code. This is not custom development for a customer. This is configuration, which means it goes faster. This is how we’re going to deploy to the mid market as well. We’ve also, if you’ve been on our earnings calls before, we’ve talked about how we’re moving away from the big one-time upfront fees and campus fees to per-user software. The market is demanding value-based pricing and value comes from people using the product.
So when we deploy it, we expand it through utilization and through people actually adopting the product. So we’ve got a common goal with our customers to get everybody using it so they realize value, we realize revenue. Again, a key message here is that we’ve taken what we’ve learned in the enterprise, the really complicated environments and we’re taking that into more deployment and into a repeatable scalable model that I’ll talk you through a little bit further here.
What I want to also as I’m going to introduce you to the products and Karim has already, I want to highlight a point that we’ve proven ourselves in the enterprise and that’s revenue. That’s great. But what it’s also doing is it’s giving us the ability to productize what we’ve done and go down market. So I’m going to work through, you know, the product that is out there today, Flow, the ones that our customers are using to book spaces, to wayfind, to interact, to get news.
This is what’s out there, that’s what’s Flow. And we’ve got this transition now that we’ve built 2.0 to transition those customers and new customers onto that. All the data that they’re creating goes into SkyView. This is not just dashboards. And this is going to be one of the demos as well. You’re going to see it’s taking that operational data and turning it into insights. That’s really exciting. Next, Events module. This is a brand new product.
It’s coming out in just a few weeks. We’ll be GA in September and we’ve solved a major industry problem. And I bet you everybody who works in enterprise is going to recognize this right away. I’m not going to talk about it now because I’ve got a couple of minutes. I’m going to just go into more detail on that then. Karim had also told you about new product Beat coming. Beat is really this tool that keeps everything on track, starting with the personal level.
This is a productivity tool, I’ll tell you that. People working in companies today are overwhelmed with the number of messages they’re getting. They’ve got systems for Jira, Slack, Teams, they’ve got things coming at them, there’s duplication all over the place and it becomes anxiety. They don’t know what to do next. So we’ve created a system that keeps everything moving, keeps you prioritized on what’s most important next, and also prepares or does the work for you to keep the team moving.
So stand by for that one that’s coming in Q4 and we’ll certainly tell you all about that as soon as it’s live. What I also want to make sure that we recognize is that we’ve got the same agentic platform driving all of this. So underneath all of this is a Sky agentic platform. So this is the thing that’s going to really, as you can see here, sense, prior—like what’s the proximity, what’s happening, what’s the priority—act, meaning do something for you.
That’s what agentic means. It’s not just giving you a message and reminding you, it’s actually in a lot of cases executing on something and then verifying. So it might give you a plan and you can approve that plan. So what we’re going to do now, we’re going to go into two videos. They are live demos of both Flow that we’ll call it this the know-me scenario. This is an employee’s view of how they’re going to go with their day. You’re going to hear me talking conversationally with the platform to do several use cases.
That’s about two or three minutes. And then we’re going to transition to the next video which is View, our SkyView analytics. And this is from the manager’s perspective. So they’re going to be there asking the strategic and insights that they want to get out of the data that they have. So with that, David, if you wouldn’t mind, let’s go to the videos and I’ll see you all back in about five minutes. Okay. I’m so glad everybody got to see that. And I get excited every time I get to demo.
That certainly feels like we’ve got the hotcakes. I say that because this is how people want to work. They don’t want the friction of having to dive into stuff. And even if you make something super easy and user friendly, you’d rather ask it through a conversation—parking lot—that I’m going to move on to events. This is our newest module. What we see on the screen here looks like chaos because it is. This is what people are living in the enterprise environments when they’re talking about managing events.
I’m not really referring to thousands of people at a large public event. Yeah, those are confusing too. But that’s not what we’re doing here. What we’re doing is we’re helping people manage events that are happening at the workplace. They happen every single day. And all of our customers, both mid level and in the enterprise, they’re going to be all-hands calls, they’re going to be sales kickoffs, they’re going to be training events. And this is really managing the part that you need a room that you can’t request yourself.
It’s not a reservable space. And so for the people that manage this on the other side, the admins, they’re dealing with everything you see on the screen, they’re going to get a calendar invite or request, they’re going to get an email, they’re going to have to open up a ticket in the catering system or even just send an email. They’re going to have to send an email or a ticket to security and AV and all of these things. And not to mention, this is not just one room in one place.
This is happening potentially around the world in ten or more places. And they have specific requirements for every location. What happens is that the event changes, things keep on piling up and there’s somebody there and when we talk to them, they’re literally in tears almost because it’s so stressful. We’re working with somebody that we’re going to launch right now. And their quote was, I am the integration layer. They said there is no system that brings it all together, which is great news for us because we have done that now and I believe that nobody has done this before because they don’t understand corporate workspace like we do.
We’ve got robust rules, we already have the user interface, we’ve already got the integration. So we are so far ahead of that. And so what we leave people with in this current state is high risk. You’ve got things that have to happen on time. It’s like a wedding, right? There has to be food, there has to be a room, there’s executives involved, there’s maybe external customers. So it’s really high-stakes, high-risk stuff. So what we’ve done to answer that, we’ve got it all into one workflow.
This is all one orchestration. You start with the user requesting everything they need. They can see what’s available, they can request what they want. In terms of space, catering, AV, it doesn’t mean they’re going to get it. It has to be approved. So there’s an approval workflow which is the real key here. It’s going to send automatic workflows for approval to the various departments that need to approve it. And at the end of the day, you’ve got one system here that’s wrapping all that up.
So this is super exciting for us because it’s an add-on, not just for our customers. We have today we’re going to market with this as a standalone as well. And we’ve got campaigns that are starting right now, full demand campaigns. We’re also leveraging the Engine Room’s platform that will help us even further promote this. So talk more about that in just a second. But as you can tell, I’m very excited. And so if there’s a slide here or a message that I want you to take away today, it’s really this.
It’s the enterprise market for us has proven our model, it’s proven our technology. We know we have product-market fit, we know we can operate in very complex environments. It’s now the mid market, the scales and I want to be really clear about something. We are not leaving the enterprise market. We’ve got great customers and we’re going to continue. I’m sure we’re the best in the world when they go looking for it. But as I described, it’s a grueling process.
It takes a while but when you win, you win big. So what we’ve done here is we’re taking everything we’ve learned in enterprise, we’ve productized it and we’re going to now take this to market and deploy it in a rapid provisioning. Okay, so this means that the connectors, as Karim described, they’re preconfigured, they don’t have to be built out, they’re going to be dropped, plug and play basically. And then we have opportunities we’ve never had before.
This is truly different. We have Engine Room as their customer base. So they’ve got growth-minded customers that this would apply to as well, the products that we’re talking about. Not only that, we’ve got their technology to super promote from a lead generation perspective that we’ve never had before. We’ve got resellers that are signed up and ready to go for this and we’ve got our marketplace partners where somebody’s going to be able to go into the marketplace where they’re already buying software, AWS or Google, buy it, start using it.
So the time to value is extremely fast which of course is going to result in scale. So an important point about this is that we’re not just recreating what we did in the enterprise and doing it down market. That would mean, you know, hey, we’re just doing smaller deals and more of them and the same hard way. It’s not that. We have productized what we’re doing. We can do it fast, we can do it easy and that’s what’s going to allow us to scale up. Okay, so what I wake up and think about every day, here’s our operating principles.
And you know, the same goes for Adam who’s running Australia. We now have one P&L. We’ve got the same set of metrics, you know, for the board and for all of us shareholders, you know, EBITDA growth, bookings, revenue growth, scale. And the way we do that and the way that we’re going to do that in our business here is we gotta deploy. So we are mid-flight, we’ve got huge projects going. They’re getting deployed flawlessly. We’re getting them out there.
That’s the number one goal. All those customers I mentioned to you, they’re going to get out there. And what does that mean? That means we’re going to start generating recurring revenue as soon as they’re out and being used. We’ve got adoption. So I mentioned to you events, literally everybody we talk to, they have this problem and it’s a burning problem. So we believe that we’re going to do a lot of upsells with our existing customers. We’re also going to do, as I mentioned, a standalone product.
But some of our customers, most of our customers, are still on our previous platform and it represents a great opportunity to enrich their experience. But also for upsells and add-ons. So things like agentic AI and other modules like the events and other things that they may not have today, those represent opportunities to increase revenue at the base. Then we’re talking about major expansion. This is what I get really excited about. We have everything I just talked about.
We’ve got pipeline deals for enterprise, we’ve got add-ons, but we’ve got this new productivity tool at the employee level that will go up and down market. This is something that’s going to apply, the product Beat, for enterprise customers. It’s going to apply for mid market. It’s going to help people do their jobs better and teams deliver which is going to really result in expansion for us. All of that combined by Q4, we’re going to have a new cohort of revenue.
These are customers that we don’t have today. They will be generating new recurring revenue and that’s the goal here. All right, so to wrap things up for me, two Engine has just become one. I think that’s really what Karim has been talking about today is that we are one company and we are way better for it. What we’ve learned in the enterprise we’re now taking into the mid market. I mentioned to you that Engine Room already has customers today that are going to be great candidates for us.
We’re going to use their tools to grow. Really the whole second part of the flywheel here is Engine Room. I think a really important message we also want to get through to everybody today is that we now have a common backbone, the Sky Agentic AI platform. Although servicing very different use cases and workflows, we are leveraging a low-cost model through bonding cortex that allow us to deliver maximum value to our customers. And so I’m going to turn it over to Adam here in just a second.
And this is great news for us as a company. It’s such a lift because Adam already has scale, he’s already got profitable growth and he’s got a great product. So I’m excited to turn it over to Adam. Adam.
Adam Laurie, General Manager, Australia
Thanks, Chris, I appreciate that. And a big hello from Australia to everyone joining us from around the world. My name is Adam Laurie and I’m the co‑founder of Engine Room and now General Manager of CXApp’s Australian operations. Speaking personally, Engine Room has been such a major part of my life for more than 13 years, so I’m really excited today to have the opportunity to introduce it to all CXApp shareholders and people on this call for the first time.
So the purpose of today: I want to bring you into the world of Engine Room, show you what we’ve built, why it works, give you an understanding of what CXApp has acquired, and, most importantly, to showcase the opportunity we have to build something collectively bigger together. Okay, so what’s our purpose and what are we here to achieve as a business? We use data, digital, and AI effectively to enable smarter decisions and unlock greater growth potential for our clients.
That’s what we do. We are revenue generators—profitable revenue generators—for our clients, and that’s why they utilize what we provide. We’re an established business and we have a very strong, proven track record. We’re Australian‑based; we serve businesses across the Australasian marketplace. At this point in time, we have a 13‑year history, first established back in 2013. We’re multi‑award‑winning across multiple facets including performance, innovation, and, most importantly for any business, our people.
What we do as a business: we’re fully integrated growth marketing solutions designed to capture high‑intent demand and drive sustainable profitability—drive growth—for our clients. So we have three major divisions: we have our martech platform, which we’ll go through shortly; fractional CMO; and then marketing as a service. What problem do we solve? And everything that we do always comes back to the genesis of what’s our purpose and what problem are we solving for a business—so why do they want to spend with us?
A business these days has difficulty building a cost‑effective and scalable customer acquisition engine. And without customers, businesses obviously struggle with growth. They have difficulty measuring marketing ROI and demonstrating commercial impact. They have disconnected business, customer, and digital data that don’t communicate and don’t speak. And they have a failure to convert knowledge, data, and AI into a commercial advantage. And that’s the problem that we solve.
We create growth marketing solutions that transform these strategies into measurable, scalable, and profitable outcomes. We build cost‑effective acquisition engines for our clients. We deliver clear, measurable ROI and commercial performance insights. We uniform data strategy and execution into a single source of truth. And we transform the knowledge and data into a sustained commercial and competitive advantage for them. The key is also what we do—and just as importantly, what we don’t do.
So in the world of digital execution, there’s two primary markets: there’s awareness and there’s intent. Awareness is when I am not aware or I’m not thinking about making a transaction or purchasing, but I might be induced by a commercial or something to think about it. We don’t focus on that market; we focus on the intent market for our clients. Those are people who are actively already out there looking for a product and service that our client provides.
And we do that because that’s the most profitable part of a market that the customer can access. They’re high‑intent customers, they’re not necessarily discount‑orientated, and they’re high‑converting—and that’s the market that we focus on for our customers. Also very measurable because it’s towards the end of their journey. Why do customers choose us? We have proven results in delivering for over 13 years now. We have cutting‑edge technology that powers smarter, data‑driven decisions.
We have solutions that show substantial and measurable ROI. We have a fully integrated end‑to‑end solution profile, and we have unmatched in‑house expertise and support. So if we look at the martech platform that I touched on, which forms the foundation of everything that we do and is so critical to our success: our technology is designed to empower marketers, owners, and advisors to make data‑driven decisions that optimize growth and drive success.
We effectively have three main parts to our platform: we have Strategize, Analyze, and Optimize. And they’re all meant to be interlinked to form a cohesive end‑to‑end solution. The purpose of Strategize: where are we going? What’s the purpose of what we’re doing here? So we have context, set the direction, define objectives. Analyze: how are we performing, measure and understand performance, maximize opportunities, identify risks. And then Optimize: what should we do next?
What are the actions that will drive improvement and gain me a commercial advantage. Those three parts are all important because ultimately, if you don’t have all three parts, then you’re going to be missing out on a key part of growth. Each module that we then build within the platform has a specific application within those sectors, and we have a whole host of different modules. We won’t go into detail today, but they have very specific applications that we can call and draw on as required when we’re engaging with our clients or the clients who are working through the platform.
So what’s important to understand about how we utilize AI and how our technology gains a commercial advantage. LLMs understand language—we all know that. The key with the Engine Room platform is it teaches AI to understand the business. And that’s the key difference. To do that, we really have to base our AI in a strong foundation. So what we do is we bring in core parts of data of a business: we bring in their business aspects—what their goals, objectives are, what their brand identity is.
We bring in their customers—understand the target market, understand how they’re trying to engage with them, understand their commercial advantages. We bring in information in relation to the competitors—what the market’s doing. And then we bring in, obviously, information in relation to their individual performance. That forms that framework for us. And then when we are driving through AI, it gives us the foundation to effectively produce stronger outcomes and stronger recommendations.
You’d know that when you’re using a lot of tools out in the marketplace, the AI may be very generic in nature. They’ll basically say these two businesses, because they’re in the same sector, want the same things—but they really don’t, because they’re all individual businesses who have different needs, different competitors, different sectors, different profit margins, etc. And without that context, it’s going to be lower quality insights and lower quality information.
Us grounding it in this real core knowledge database enables our customers to gain a significant commercial advantage. The other thing important is that when we’re using AI, it’s a continuous learning application. We store all this data, and every month that we’re storing this data for our clients, we are improving the functionality and the output of what it can deliver. So it’s a living, breathing learning tool that enables us to continuously move forward with our clients.
And that’s a really important part—both the knowledge center and the time aspect—to continuously gain that commercial advantage for our clients. And that’s where you get back to ultimately a prompt and answer versus knowledge and action. So traditional AI: give it a prompt, and then it’ll be like, here’s the answer that we recommend—and it’s a very generic prompt and generic answer because it’s done in the context of everything and everyone. Whereas in Engine Room, we have that specific knowledge and we have that specific reasoning from learning, and that enables us to do a very high‑quality action specific to that client’s needs. So today we’re going to show you an example of the platform which is going to go through a few modules. The client I’m going to show you is a smaller client, but they’ve kindly enabled us to showcase their data. But it doesn’t matter whether it’s a small or a larger client; the same principles apply. And I’m going to give you an example into just some of the modules and how we apply them and how we discuss them when we talk with our client. So, David, if you’d like to press play. Thanks. I hope everyone enjoyed that. Okay, so why Engine Room and CXApp? So CXApp’s Australasian growth engine—we are looking to be CXApp’s Australasian growth engine. Karim really touched on that before. We are a business that has grown substantially year on year, that has generated ongoing growth strategies.
We target customers who are in that 5‑to‑500 historical customer range. Average client yield is around about $200,000 per annum. We have 93% recurring revenue and the average client extends beyond four years in life. Our customers are across diversified industry sectors—professional services, home services, manufacturing, industrial, etc. So we have a strong, diversified mix, which is a great foundation for the next stage of our growth. We have a proven track record of scalable growth year on year.
As you can see, over the last five years we have consistently grown—and that’s profitable growth. We consistently move forward with, importantly for any company, a proven team, and we have leadership who are staying on board. We have an award‑winning culture which has been recognized, I think, for the last five years. An experienced leadership, and we have a very strong specialist capability and capacity who are being retained across technology, AI, data engineering, and growth marketing expertise.
What does it mean for the future? Well, there is enormous growth opportunity, even in the Australasian marketplace. We are in a sector—we are fortunate to be in a sector—that has high growth in all capacity, whether it be martech, the fractional CMO, or marketing as a service. And even in the context of Australia, even though we turn over $8 million, the context is that the growth opportunities in Australia are so significant. And that’s one of the things that is exciting about CXApp and Australia coming on board, is that it will enable us to hopefully unlock so much of that growth opportunity that we know is available.
So what’s the next steps from here and the pathway forward? Accelerating Engine Room with CXApp—combining Engine Room’s expertise and customer relationships with CXApp’s agentic AI capabilities—so we can look to improve. We already do a semblance of AI, but we know that CXApp has strong agentic capabilities, and we have the capability and capacity to look where that can be integrated and improve what we do as a business. We will be looking to accelerate our product development, once again leveraging off CXApp’s expertise, and expand our data and intelligence capabilities.
To that end, enduring business knowledge plus CXApp agentic AI—we’re looking to improve the intelligence, the reasoning, and the action outcomes. To give you some context from a development architecture: at the moment we have done a lot in the data, the source of truth, and the business knowledge, which I touched on before. And we’ve started with the reasoning and the decision engine. What we look for in the future roadmap is to strengthen the reasoning and decision intelligence, but then also look at taking the next step—and this is where CXApp’s capabilities come into play—with agents and autonomous business execution, which we see as a big opportunity for the next steps forward. So the commercial opportunities: we are strategically positioned to capitalize on key market opportunities that will drive future growth and value creation. We look to expand into new verticals; growth through strategic partnerships and channel expansion; technology innovation to increase customer value, retention, and lifetime value; look to use AI to drive efficiencies and scalability and profitability; and strengthen the competitive differentiation between us and other people out there in the industry. But as I touched on before, the capacity for growth is just enormous as long as we execute to that high level. I just want to say thank you. Lovely to meet everyone today. Lovely to introduce the Engine Room story. We’re very excited about it and we’re very excited about the next steps. I’ll hand it over next to Zoe, who we’re going to be doing a fireside chat with.
Zoe Chen, Workplace Strategist at Felton & Company
Hi, everyone. So my name is Zoe Chen. I’m a workplace strategist at Felton & Company. I spend most of my time inside companies while they’re in the middle of changing how they work. Not the strategy deck version, the actual version. So it’s the part where somebody has to tell 300 people that they’re losing their assigned seats and will be sharing desks in the future. What’s really interesting in this particular moment is that everybody in the building is talking about AI, even when the project is about building out the physical space.
I want to give you three things I think are true right now. They’re not predictions, they’re just what I keep running into. And then I’ll invite Chris, Adam and Corin to ask me some questions. So the first one: here’s what I would have told you 10 years ago, and I would have been right. Automation starts at the bottom and works its way up. That’s the pattern. The assembly line, the ATM, self-checkout, the scanners in a warehouse. Machines were good at doing the same physical thing over and over and bad at basically everything else.
So the safe advice was get more education, get further from the repetitive stuff and you’ll stay ahead of it. That was the real deal for about 40 years. And then this technology showed up and completely ignored it. Because it turns out, the things that took us the longest to learn—writing, analyzing, summarizing, coding—those are cheap ones to replicate now. And the thing that a kid can do without thinking, like walking into an unfamiliar room and picking up an oddly shaped object, those are still incredibly difficult.
There’s good data on this now, not just anecdotes. Anthropic has been publishing something called the Economic Index, where they analyze millions of real conversations with their AI to see what people are actually using it for. Mapped against the government’s occupational database, what comes out is pretty clear. The heaviest users cluster in mid- to high-wage occupations; both very low-paying and very high-paying jobs show low AI use because those tend to be the ones involving a lot of manual dexterity.
Their example is shampooers and obstetricians, which tells you something about how little these two have in common, except that both require hands. It landed on information work, the desk jobs, and it’s not creeping in slowly. About half of all jobs have already seen at least a quarter of their tasks touched by AI. The flip side is that there is a large part of the workforce sitting in a near-zero exposure zone. Electricians, plumbers, HVAC technicians, mechanics.
So if the job requires you to physically be somewhere and put your hands on something, this wave mostly isn’t coming for you. But being protected isn’t the same as being unconstrained. Think about the three-truck plumbing company. What’s actually stopping that from becoming a ten-truck business? It’s not the plumbing. They’re great at plumbing. It’s everything that happens away from the job site. Whether the quote went out the same day or four days later, whether somebody followed up on the estimate from two weeks ago, whether the reviews are getting answered, whether there is an extra lined up when this one is done.
So there’s a whole back office of a small business and it’s the part that the owner is least equipped for and probably least interested in. And that’s the frustrating bit. There’s no shortage of software for them. There is a tool for the quoting, a tool for the scheduling, a tool for the reviews, a tool for the follow-up. But that’s the problem. Every one of those needs to be set up, connected to others, and babysat by somebody. Nobody started an HVAC business because they wanted to become a CRM administrator.
The choice they’ve been offered for 20 years has basically been stay small or spend your evenings learning the software. That’s what feels different to me about this wave of tech innovation. The promise isn’t another tool to master. It’s the outcome without the operating burden. And if that lands, the small operators really can get a back office that used to require real scale to afford. Okay, second thing. Everyone on this call probably already used personalized intelligence at least three times before breakfast and didn’t even notice.
Once your phone sorted your emails before you looked at it. Your news app put the top three stories that you actually care about on the very top. Your grocery apps already know that you were low on coffee. And your maps app routed you around something before you even knew that it was there. And none of it felt like technology. It just feels like things are working. We’ve gotten completely used to systems that know us. And when you walk into the office, it all kind of stops.
When every app is doing its own thing, nothing knows you, nothing talks to anything else. As Chris said earlier, you are the integration layer. You are the one holding it together. Now, I want to be fair here. AI has already changed a huge amount about how we handle information. Notes, emails, transcripts, catching up on a meeting you missed. That part is real and people feel it every day. What it hasn’t done yet is meet people where they actually are—in the building, in the physical space.
The building doesn’t know you’re in it. The room-booking system doesn’t know your whole team came in today. Your calendar doesn’t know you’re on the other side of campus with eight minutes to get to your next meeting. And this is the part I push back on. When people talk about workplace productivity, the exhausting part of the day usually isn’t the hard problem that you signed up for at your job. It’s everything around it. Finding a room, doing the time zone math, figuring out who’s actually in today, working out where to sit.
When half of your team is scattered across three floors, every one of these takes 15 seconds and none of them are your job. But you do 40 of them. And by three in the afternoon, you’ve burned real mental energy on decisions that should have been made for you. Think about what GPS actually does for you. It’s not that you wanted a better map—you never wanted a map. You wanted to arrive. You wanted to stop thinking about the path. And that’s what people want out of their workday.
Not more tools, but fewer decisions. And none of this is new, really. Work always lags behind life. It did with the phones in your pockets and it did with video calls. It did with every tool that felt normal at home for years before it felt normal at the office. So people improvise, they find a workaround. They use AI on their phones, on tools nobody bought them because it makes their workday a little better. And nobody made them do that. There was no rollout, no training, no email from IT.
They found something that helps and they kept using it, which is usually how you know what’s coming. What people do on their own eventually becomes what they expect at work. And right now there’s a real gap between the two. The last one. There’s some research that’s been getting passed around about how AI pilots don’t show a measurable return. And people have taken that to mean that the technology doesn’t work. I think it’s worth knowing what that study measured.
It was an MIT report. It looked at whether a pilot moved the P&L within about six months. And a lot of what it looked at was sales and marketing, where six months is still mid-cycle. So they were essentially measuring before the thing finished happening. A new hire doesn’t move P&L in six months either. So it’s not a damning finding. It really is just a short window. Within that same study, there’s a second number that almost got no attention. When companies brought in a specialist to deploy, it reached production about two-thirds of the time; when they built it themselves, about a third. So we’re looking at twice the success rate here. And here’s why it’s interesting. It’s not a technology gap. Everybody has access to the same models. You can buy the same capability on a credit card. The gap is entirely in the execution. A few reasons for it, and none of them are exotic. The specialist has done it before. They solved the integration problem, the permissions problem, the governance problem, a hundred times.
The internal team is solving each one for the first time while also doing 17 other things. The tools that work great for you individually often stall inside a company because they’re flexible, but they don’t learn the specific workflow you dropped them into. And internal projects almost always underestimate the boring half. The plumbing, the data access, the edge cases. Demos run on clean examples. Real companies are nothing but edge cases. That’s how you end up in pilot purgatory for a year and a half.
There’s also a control thing. Building it yourself feels like control. In practice, it usually means fewer people, slower iteration and a pile of technical debt. But the reason I find this encouraging rather than discouraging is that none of those are technology problems. Every single one is solvable by a team that’s done it before. Nobody’s waiting on a breakthrough. The capability is here. The practice is just catching up. I’ll say one honest thing though, because I don’t think it helps anyone if I only give you the tidy version of the story.
Buy-first isn’t universal. If you’ve got proprietary data a general model can’t touch, or a genuinely unusual workflow, or you’re in a regulated high-risk situation, building can be the right call. It’s just not the default anymore. So, three things. The pressure landed on information work, not physical work. Which means the businesses that were hardest to grow might be the ones this helps first. And second, we all got personalized intelligence everywhere in our lives except the place we spend 40 hours a week.
That gap is the opportunity. Lastly, the technology is proven. What’s still being worked out is how you put it in, and that’s the variable that decides whether any of this pays off. Happy to get into any of it.
Chris Wiegand, General Manager, North America
Yeah. And thank you, Zoe. That’s great table-setting for us in the context, and we’re really lucky. Zoe is flying around probably the world, but I’ll say at least the States, going to different customers, and she’s really seeing what’s happening out there. And so I think you mentioned that these are not just trends that you’re reading about, you’re actually seeing them. I was really taken away by a lot of that. What we’re going to do now, just to make this more interactive, we’re each going to ask you a question.
We have a bit of a conversation. This is the fireside chat part of things. We’re just going to build on everything you just talked about. Why don’t we go in the order that you started from. Adam, you’re the expert on trades and with your business. So go ahead.
Adam Laurie, General Manager, Australia
I think you guys call it home services over there. And Zoe, thanks for the chat, and I look forward to taking the short flight over to Australia at some point. My question is: trades and home service businesses generate enormous amounts of operational and customer data every day. Where do you see the biggest opportunity for AI to turn that data into better decisions and ultimately better business outcomes?
Tony
Yeah, that’s a great question. I think the thing is the data is all there. That’s the thing. Every job a trades business does throws off information: what broke, what it took to fix, how to actually get customers, what venues actually work. But it’s scattered. It’s in a scheduling tool, in a text thread, in a stack of invoices, in somebody’s post-it notes. A fair amount of it is just in somebody’s head. So the person who has to pull all of that together and make sense of it usually is the owner, who might be on the roof all day.
And if it happens at nine at night, or if it happens at all, it’s not really analysis at that point. It’s whoever’s still awake trying to remember whether the job was done successfully. I think that’s the gap. It’s that the data exists, but nobody in the business had the bandwidth or the training sometimes to really sit with it and find the pattern. And the patterns are also right there: which jobs are actually making money once you count the drive time, callbacks, and things like that; which estimates are consistently wrong and by how much; and what kind of work you should be taking more of and which you keep saying yes to out of habit. I think that’s the opportunity. It’s maybe less fancy or exotic than it sounds. It’s just showing a business what it already knows but has never been able to see in one place, and turning that into something they can really act on on Monday morning. And for this to be not something that just relies on the owner, but as the business grows and scales, it could become shared understanding that the team can mobilize together on.
Karim, CEO
Thanks, Tony. I appreciate that. Sorry I jumped in. I’m excited. As a person that’s been spending the last 20 years on maps, indoor maps, you struck a chord with me. Not just indoors—when I’m driving, like nobody really cares about how to get there. I mean, remember we had MapQuest and you had to really figure out; I just wanted to arrive. You got the blue dot near the center of the universe, and it’s so easy now. I mean, it’s actually at a point that we don’t have to think and, you know, you were building on what I was talking about: being the person, being the integration layer.
And then you started to quantify what that coordination tax, that overhead of the things that we don’t even think about. Yeah, it’s easy, I can just look and I can find a place to go, I can navigate things. But, you know, we’ve talked a lot about, like, sort of the neuroscience behind that, and you were really getting at it—like, this is actually impacting productivity. We also know that it’s like a screeching slide into sandpaper. You’re coming to work, you’ve got all these great tools like Waze and everything that helps you navigate seamlessly.
And then you get in the building, you’re like, where did it go? Now I’m back to the manual stuff. If we can get to a place where the building truly knows me as well as my phone and my personal tools, and we can get over that overhead tax of people having to figure those things out, like, what do you think? What are you seeing in the research as to, like, what would that mean? I mean, I’m sure there’s business outcomes. What’s the extent of it on, you know, the human experience and maybe the business outcome?
Zoe Chen, Workplace Strategist at Felton & Company
Yeah, I mean, I think the top thing that’s jumping out for me is decision capacity, right? We—human beings, as just a normal, typical human being—there’s a finite amount of good decisions that I have on a daily basis. And right now, I think a lot of that bandwidth is kind of wasted on the minute details that just have to surround the actual job itself. So being able to gain back that cognitive reserve to focus on the things that are more important, that are more critical—synthesizing, really understanding patterns, creating—that is, I think, what’s really out there.
I would add another really important aspect that’s just starting to surface is also the mental space for people to focus on what makes us human, which is building connections and relationships with other people. I think hybrid work and digital-first ways of working have been fantastic with all of the technologies making sure that people can still get the work done no matter where they are. But when people are in person with each other, in a physical building, what you really want people to have—not only the time but also the mental capacity to do—is have a real conversation with somebody and actually start to build that connection, build a community, build an environment that’s helping each other to learn. So I think those are all really critical moments that, in an ideal world where AI frees us from the minute details that I have to decide, then I can just really focus on experiencing the present and all of the connections.
Chris Wiegand, General Manager, North America
Yeah, you just made me think about something, actually. When you’re sort of adding this all up as a thought experiment, what if—you said earlier, maybe it’s 10 minutes a day, maybe it’s 20 minutes, I don’t know what the exact number is—for the coordination tax. But what if I traded those minutes exactly for high-value moments, like some of the customers call them, moments that matter, right? So if I wasn’t spending 10 minutes doing all this mundane friction tasks of booking meetings or whatever, and I had a meaningful conversation with you, and maybe we found out that we love the same food or something—like maybe we found out something about a project. So I think that’s an interesting idea just to go: if I could trade minute for minute for something that’s high-value—strategic, culture, connection. It’s very subjective, I get that, but there could be some pretty interesting outcomes. All right, we’ll parking lot that one, and Karim, I’ll turn it over to you.
Karim, CEO
Yeah. It’s a fascinating conversation. Thank you, Zoe, for joining us. I think your last trend was on the deployment. I don’t want to throw a curveball, but I want to put the context in terms of the next generation—younger, my kids or others who are just coming into the workforce, who have been coding for half their life. They’re 18, but they’ve been coding for more than half their life. They’re also already experts of AI. They already know how to code it.
When you think about deployment, every one of them is their own white coder, is their own developer, thinks they’re the best thing than anybody else. So how do you see this evolving in terms of—we see new models coming every day, we see new tools coming every day, everything changes so fast—how do you see this to be a scalable motion from a deployment? How does it get scaled not with millions of different things, but a motion that you feel like is going to get deployed at scale for the enterprise?
Zoe Chen, Workplace Strategist at Felton & Company
Yeah, I’ll answer that part based on what I can see from inside companies, which is more on the adoption side rather than the distribution side. And I think, and here’s where mid-market is becoming really interesting, right? Because it’s the segment that moves the fastest. They may not be the most resourced, but they are the fastest. They might not have an AI center of excellence; they don’t have a two-year roadmap, right? But that turns out to be an advantage because there are fewer people that you need to agree to make a move on something.
So what they don’t have is someone whose job is to make this work, right? In a big enterprise—you all have that experience—in a big enterprise, there’s a team. In a 200-person company, it’s somebody’s fourth priority. So the thing that has to be true for mass deployment is that it cannot require an owner or a champion, a project plan, all of the complicated stuff. It doesn’t scale into that segment. And what it has to do is it has to spread the way things actually spread in a smaller company.
I love the example that you mentioned with a younger generation that are essentially natives, right? How do they know which app is the trendiest one to use? How do they know which video editing app is the best? Somebody uses it and it’s visible, right? It visibly saves some time or it visibly delivers better results, and the person next will go ask them, oh, what is that thing that you used? Right. That’s the whole mechanism—not necessarily orchestrated rollout or training session, but just one person’s day getting noticeably better in front of other people.
I think that would be, from a behavioral perspective, what would really help with adoption.
Karim, CEO
No, that’s interesting, and I agree with you. I think it’s that we see that in our enterprise business where we get referrals, but I think this is a more viral set of referrals that happen just because somebody uses it and finds it amazing, and then the next person sees the same thing. So cool.
Chris Wiegand, General Manager, North America
I think, Karim, on that note also, you know, this is where I was talking about value-based selling. The whole market has shifted. We are in 30-day-or-less commitments in a lot of cases on the products that are coming out. People have to see value. In mid-market, I think the threshold is that much higher. It’s like, yeah, this is working for me. Nobody’s forcing me to use this. I’m going to use it, I’m going to love it, I’m going to tell people. And I think the onus is on companies like us—the ones that are deploying it.
We have to make it, first, easy to deploy. There’s no patience for these giant integrations at smaller companies, and people have to love it. I mean, that’s the whole thing. And it has to stay fresh and be used all the time. So yeah, anyways, there’s so much more we could talk about. I’m going to close off with Adam because when I first met Adam, he and I have a joint background of working at a large telco—like, you were at Telstra; I was at Sprint.
And then, progressing through our careers, we’ve gone to the mid-market. So maybe, Adam, you want to close off to say: what is your experience with the mid-market and how do you see this evolving?
Adam Laurie, General Manager, Australia
I love the mid-market because they make decisions rapidly and they’re very much focused on outcome. So as long as everything you do is related back to an outcome—not a metric; it’s an actual business outcome—then they don’t have to sit there and go, well, it’s not in this year’s budgets, whatever. It’s like, well, that makes sense. If I spend $2, I make $10. Go. Right. I could have happily built something for enterprise. But I was like, no. Mid-market is where the acceleration is. Mid-market is where the adoption is. Mid-market is where the speed is. But you are right, Zoe, in that part of it is recognizing that they don’t have that support layer internally. For us, we’re ever dealing with the owner or one level down, perhaps.
Who indirectly deals with the owner, right? Or directly deals with the owner. So that’s why the model that we do—in mid-market, you have to basically be that capacity. To enable them to do it. And you just have to accept that. And that’s built into the model.
Chris Wiegand, General Manager, North America
All right, well, thank you so much, Zoe. We could talk for hours—I’m sure we will. Great conversation, great insights, and I’m sure we’ll have you back as a guest again. And thank you very much. I think we’re going to now move to—Karim has some closing words, and we have some more Q&A, so Adam and I will stick around.
Karim, CEO
Yep. So I’ve got a couple questions that came in, so I’m going to get you guys’ help on that. So one question came in and I’ll start with it, and then, Chris, you can double down. Has the Google partnership helped at all, and how? It’s a very good question. We’ve been using Google on both sides, helping us with the cloud infrastructure and helping with getting all our clients—most of them are on Google Cloud, which is great—and getting them the advanced products and access.
Then we’ve also, as Chris mentioned, been working on the Google Marketplace to launch the mid-market, which we think is a huge opportunity. So we work regularly with the Google team. But I’ll tell you one thing that happened. I think Chris was showing you the Events module, and I’m proud to say our engineering team, working with the Google team, got that product done literally in—Chris has the exact numbers, but I think it’s within a quarter or less.
So it is an amazing ground zero to now production. So maybe, Chris, you want to expand how Google helped you there.
Chris Wiegand, General Manager, North America
Yeah. So I also want to make something clear—that didn’t go so fast because it’s easy. It went so fast because, A, we’ve got a lot of IP around this, I mentioned in my presentation. Over the last number of years it is highly sophisticated, highly proprietary, and which is why we win these complex deals—so we understand how things are managed in the workplace. So we had all of these parts and pieces. Don’t forget we also have integrations with these customers already into their core systems, their ticketing systems, their directory systems.
The Google team, working with our partners and our internal team, we glued it all together and created what is a seamless, orchestrated workflow. Yes, it went fast and it’s new, but it’s really a combination of our features and modules that’s very specific to how our customers do business. Now, where does Google come in next? It’s a hyperscaler. First of all, we’re working in secure environments. We have ultra-high security on our own platforms and for our customers.
And next we’re going to be in the marketplace. So when people—part of the whole buying cycle is going through contracting and going through all those motions and then delivering—well, that’s all now going to be through the marketplace so that somebody can just sign up, buy it, do a click-through EULA, pay for it, get the product. There might be a couple integrations afterwards, but the time-to-value is super important. And for all those reasons, this is really where we go from small quantity to prime-time scale.
Karim, CEO
That’s great, that’s great. Next question I have is, what are the major synergies between legacy biz, and what do you expect the go-forward OPEX levels to be, quarterly? I’ll start, then I’ll hand it off to Adam to give his input as well. But I can tell you right now—Adam can tell his philosophy of how he runs his OPEX models. Right. But I would tell you right now is that there’s a huge opportunity for synergy as we combine the businesses. We have the common infrastructure, the cloud infrastructure we talked about.
Adam also, by the way, uses the Google ecosystem extensively, not only for the services but also for Google Ads and other things he does with his clients. So there’s an expanded relationship there. So there’s a synergy factor there in terms of relationship. But all in all, when we think about our business, we’re going to leverage Adam’s distribution channel. He’s going to leverage our enterprise access and channel. So there are going to be lots of synergies there on core infrastructure and locations.
You know, he’s based in Manila, we’re in Manila as well. There are synergies there. As we think about, you know, growing the teams, it’s one team under the Sky umbrella, and leveraging all the shared infrastructure costs, we think there’s significant opportunity there. So those realizations, as I mentioned in my chart, are going to happen over the next six to twelve months. Some actually are happening this quarter, as you can see some of the impact, but they’re going to start happening very quickly in Q3 and Q4 and early next year as well.
I’m excited about that. But maybe, Adam, you want to talk about your OPEX strategy, how you’re managing your OPEX.
Adam Laurie, General Manager, Australia
Yeah, and I think the important thing is that business model has always been about profitability, sustainability moving forward. We last took capital on board, I think, seven or eight years ago from memory. So, you know, we have always focused on, from an OPEX point of view, that we would be significantly below the revenue side so we can invest in a sustainable way. So, look, I think the key is what Karam touched on before, and this is the pathway that we’re going through at the moment.
What’s the operational cost that can be reduced as a percentage that we cross over. And I think that’s really the process that we’re going through at the moment, you know, because there’s a lot of aspects of that. But I’m sure we’ll be reporting on those in the future as we succeed in that area.
Karim, CEO
Okay, last question. I’ll give it to Chris. So, Chris, question is, you announced a lot of great new products. You’ve got the Flow and Beat and Events and stuff. What is your competitive moat? For a small company like CXApp, how are you creating the competitive moat? Because a lot of people are vying for those kinds of products. So what is the Sky moat?
Chris Wiegand, General Manager, North America
Yeah, we’ve got a number of different things here and I touched on it earlier, and one of them is just IP. I’ll start with—and I’m not relying on this—but we’ve got enterprise customers, we’ve proven technology, we have been deployed in some of the world’s toughest, most complex environments at scale. This is not just a demo happening. We’re talking about thousands and thousands of users at these organizations and reliably delivering that. Beyond that, when I really think about today’s market, it’s all about our ability to differentiate.
And how do we do that? Well, one of them is even on the cost side. When we talked about our agentic AI bot and Cortex, it’s truly different in the market. We are able to do LLM at a fraction of the cost. So something that somebody’s doing in one of the main LLMs is costing a cent and not, you know, tens of dollars. So that’s a huge moat. We’ve got the IP around context and spatial awareness. Okay, so this is something that other companies do not have.
We understand what’s going on in space. We’ve got all these integrations, which is giving us connectivity, and it’s increasing, you know, enhancing the user experience. It’s also creating all that data. So when you saw me demoing about asking these questions by conversation and getting highly, you know, analytical or insightful answers, that’s coming through all of those integrations. We’re really at the center of this. The company grew up bringing together events, maps, workplace, and when this became CXApp, it was based on delivering agentic AI.
I think we’re leaps and bounds ahead of understanding how to deliver agentic AI. You said it right at the beginning of the presentation. This is not another chatbot or an assistant. This is an agentic solution that does things for you, and that’s what people want. We don’t want the overhead of having to answer everything manually or set up a meeting manually. It’s going to do it for us. At the end of the day, if you ask me, I think it’s user experience, and we talked about it all through this.
People are loving the product and they tell people about it, and it becomes viral within those organizations. And, of course, all the referrals that we get because people are super happy with the products.
Karim, CEO
Yeah, great. Well, thank you, gents. Really appreciate it. We’re going to head to my last slide or last two slides, and I know we’re at the top of the hour, but we’ll go a few more minutes here. Thanks, Chris. Thanks, Adam. All right, so let me leave you all with this. I spend my career around major technology transitions, and I believe agentic AI will be one of the most consequential. And I don’t mean that lightly. And I don’t believe the winners will simply be the companies with the biggest models.
I believe enormous value will be created by companies that understand context and turn that context into action. That is the company we are building—that is what CXApp is about. We started with the workplace. Now we’re expanding from place to person to business. These are the three forms of context: Place through our Flow product, which tells you where and how people work; Person through Beat—what an individual and team need to accomplish and what should happen next; and Business—how companies acquire customers, convert demand, and grow. That business context is significantly strengthened by Engine Room, as we talked today. We are building the agentic operating layer for how companies work and grow—full stop. And we’re focused on it. We’re really excited about it, as you can see. I want to leave you with three things I said at the start of the call, and thank you for your patience to be with us for nearly two hours here.
But if you remember only three things from today’s call, I want them to be these. Number one, we have changed the scale of CXApp Sky. We have moved from roughly a $4 million annualized revenue company at the beginning of this year to a combined platform with more than $12 million of annualized revenue scale, and now we serve both enterprise and mid-market customers. Number two, Sky 2.0 is moving from vision to commercial execution. The platform is in production.
We have customer deployments starting. We have major renewals. We have new multi‑year enterprise wins, and now we have Engine Room’s customer base as an additional channel through which to prove and distribute our new AI products. Number three, we have a clear operating priority: profitable growth. The next phase is not simply about adding revenue. It is about combined double‑digit growth with increasing recurring revenue, stronger software mix, operating leverage, and disciplined execution.
Our directional objective is to move toward break‑even in the second half of 2027 and profitable growth beyond that point. So I would categorize Q2 this way: Q2 2026 is the quarter in which Sky began moving from a workplace software company with an agentic AI vision into a scaled agentic AI platform with enterprise proof, mid‑market distribution, and a credible path to profitable growth. The acquisition creates scale. Sky 2.0 creates the opportunity for operating leverage, and execution from here determines the value we create.
Thank you to our customers, our employees, our partners, and shareholders for your continued support. We look forward to updating you on our progress next quarter—we plan to do that in November—and then we are also looking at another investor session at the end of the year or start of the year of 2027. But we’re excited about Sky, and to the Sky and beyond. Thank you, everybody. Operator, you may close the call.
Disclaimer: This transcript is provided for informational purposes only. While we strive for accuracy, there may be errors or omissions in this automated transcription. For official company statements and financial information, please refer to the company’s SEC filings and official press releases. Corporate participants’ and analysts’ statements reflect their views as of the date of this call and are subject to change without notice.
Recent Comments